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中国经济发展、环境污染与人类健康之间的动态联系。

Dynamic linkages among economic development, environmental pollution and human health in Chinese.

作者信息

Li Ying, Lin Tai-Yu, Chiu Yung-Ho

机构信息

Business School, Sichuan University, Wangjiang Road No. 29, Chengdu, 610064 People's Republic of China.

Department of Business Administration, National Cheng Kung University, No. 1, University Road, Tainan, 701 Taiwan R.O.C.

出版信息

Cost Eff Resour Alloc. 2020 Sep 7;18:32. doi: 10.1186/s12962-020-00228-6. eCollection 2020.

Abstract

BACKGROUND

Research on the relationships between economic development, energy consumption, environmental pollution, and human health has tended to focus on the relationships between economic growth and air pollution, energy and air pollution, or the impact of air pollution on human health. However, there has been little past research focused on all the above associations.

METHODS

The few studies that have examined the interconnections between the economy, energy consumption, environmental pollution and health have tended to employ regression analyses, DEA (Data Envelopment Analysis), or DEA efficiency analyses; however, as these are static analysis tools, the analyses did not fully reveal the sustainable economic, energy, environmental or health developments over time, did not consider the regional differences, and most often ignored community health factors. To go some way to filling this gap, this paper developed a modified two stage Undesirable Meta Dynamic Network model to jointly analyze energy consumption, economic growth, air pollution and health treatment data in 31 Chinese high-income and upper-middle income cities from 2013-2016, for which the overall efficiency, production efficiency, healthcare resource utilization efficiency and technology gap ratio (TGR) for all input and output variables were calculated.

RESULTS

It was found that: (1) the annual average overall efficiency in China's eastern region was the highest; (2) the production stage efficiencies were higher than the healthcare resource utilization stage efficiencies in most cities; (3) the high-income cities had lower TGRs than the upper-middle income cities; (4) the high-income cities had higher average energy consumption efficiencies than the upper-middle income cities; (5) the health expenditure efficiencies were the lowest of all inputs; (6) the high-income cities' respiratory disease and mortality rate efficiencies were higher than in the upper-middle income cities, which had improving mortality rate efficiencies; and (7) there were significant regional differences in the annual average input and output indicator efficiencies.

CONCLUSIONS

First, the high-income cities had higher average efficiencies than the upper-middle income cities. Of the ten eastern region high-income cities, Guangzhou and Shanghai had average efficiencies of 1, with the least efficient being Shijiazhuang. In the other regions, the upper-middle income cities required greater technology and health treatment investments. Second, Guangzhou, Lhasa, Nanning, and Shanghai had production efficiencies of 1, and Guangzhou, Lhasa, Nanning, Shanghai and Fuzhou had healthcare resource utilization efficiencies of 1. As the average production stage efficiencies in most cities were higher than the healthcare resource utilization stage efficiencies, greater efforts are needed to improve the healthcare resource utilization. Third, the technology gap ratios (TGRs) in the high-income cities were slightly higher than in the upper-middle income cities. Therefore, the upper-middle income cities need to learn from the high-income cities to improve their general health treatment TGRs. Fourth, while the high-income cities had higher energy consumption efficiencies than the upper-middle income cities, these were decreasing in most cities. There were few respiratory disease efficiency differences between the high-income and upper-middle income cities, the high-income cities had falling mortality rate efficiencies, and the upper-middle income cities had increasing mortality rate efficiencies. Overall, therefore, most cities needed to strengthen their health governance to balance economic growth and urban expansion. Fifth, the average AQI efficiencies in both the high-income and upper-middle income cities were higher than the average CO efficiencies. However, the high-income cities had lower average CO emissions and AQI efficiencies than the upper-middle income cities, with the AQI efficiency differences between the two city groups expanding. As most cities were focusing more on air pollution controls than carbon dioxide emissions, greater efforts were needed in coordinating the air pollution and carbon dioxide emissions treatments. Therefore, the following suggestions are given. (1) The government should reform the hospital and medical systems. (2) Local governments need to strengthen their air pollution and disease education. (3) High-income cities need to improve their healthcare governance to reduce the incidence of respiratory diseases and the associated mortality. (4) Healthcare governance efficiency needs to be prioritized in 17 upper-middle income cities, such as Hangzhou, Changchun, Harbin, Chengdu, Guiyang, Kunming and Xi'an, by establishing sound medical management systems and emergency environmental pollution treatments, and by increasing capital asset medical investments. (5) Upper-middle income cities need to adapt their treatment controls to local conditions and design medium to long-term development strategies. (6) Upper-middle income cities need to actively learn from the technological and governance experiences in the more efficient higher-income cities.

摘要

背景

关于经济发展、能源消耗、环境污染与人类健康之间关系的研究往往集中在经济增长与空气污染、能源与空气污染之间的关系,或者空气污染对人类健康的影响。然而,过去很少有研究关注上述所有关联。

方法

少数研究经济、能源消耗、环境污染与健康之间相互关系的研究倾向于采用回归分析、数据包络分析(DEA)或DEA效率分析;然而,由于这些是静态分析工具,分析未能充分揭示随着时间推移的可持续经济、能源、环境或健康发展,未考虑区域差异,且大多忽略了社区健康因素。为了在一定程度上填补这一空白,本文开发了一种改进的两阶段非期望元动态网络模型,以联合分析2013 - 2016年中国31个高收入和中高收入城市的能源消耗、经济增长、空气污染和健康治疗数据,并计算所有投入和产出变量的总体效率、生产效率、医疗资源利用效率和技术差距比(TGR)。

结果

研究发现:(1)中国东部地区的年平均总体效率最高;(2)大多数城市的生产阶段效率高于医疗资源利用阶段效率;(3)高收入城市的TGR低于中高收入城市;(4)高收入城市的平均能源消耗效率高于中高收入城市;(5)健康支出效率在所有投入中最低;(6)高收入城市的呼吸系统疾病和死亡率效率高于中高收入城市,中高收入城市的死亡率效率有所提高;(7)年平均投入和产出指标效率存在显著区域差异。

结论

首先,高收入城市的平均效率高于中高收入城市。在东部地区的十个高收入城市中,广州和上海的平均效率为1,效率最低的是石家庄。在其他地区,中高收入城市需要加大技术和健康治疗投资。其次,广州、拉萨、南宁和上海的生产效率为1,广州、拉萨、南宁、上海和福州的医疗资源利用效率为1。由于大多数城市的平均生产阶段效率高于医疗资源利用阶段效率,因此需要加大力度提高医疗资源利用效率。第三,高收入城市的技术差距比(TGR)略高于中高收入城市。因此,中高收入城市需要向高收入城市学习,以提高其总体健康治疗TGR。第四,虽然高收入城市的能源消耗效率高于中高收入城市,但大多数城市的能源消耗效率在下降。高收入城市和中高收入城市之间的呼吸系统疾病效率差异不大,高收入城市的死亡率效率在下降,中高收入城市的死亡率效率在上升。因此,总体而言,大多数城市需要加强其健康治理,以平衡经济增长和城市扩张。第五,高收入城市和中高收入城市的平均空气质量指数(AQI)效率均高于平均一氧化碳(CO)效率。然而,高收入城市的平均CO排放量和AQI效率低于中高收入城市,两个城市组之间的AQI效率差异在扩大。由于大多数城市更关注空气污染控制而非二氧化碳排放,因此需要在协调空气污染和二氧化碳排放处理方面做出更大努力。因此,给出以下建议。(1)政府应改革医院和医疗系统。(2)地方政府需要加强空气污染和疾病教育。(3)高收入城市需要改善其医疗治理,以降低呼吸系统疾病的发病率和相关死亡率。(4)杭州、长春、哈尔滨、成都、贵阳、昆明和西安等17个中高收入城市需要通过建立健全医疗管理系统和应急环境污染处理机制,并增加固定资产医疗投资,优先提高医疗治理效率。(5)中高收入城市需要因地制宜调整治理措施,制定中长期发展战略。(6)中高收入城市需要积极借鉴效率更高的高收入城市的技术和治理经验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c962/7487810/6a033ff2ce70/12962_2020_228_Fig1_HTML.jpg

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